Molecular Dynamics

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Period ending 2026-09-21

5 new papers

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Period ending 2026-09-14

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Period ending 2026-09-07

7 new papers

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174 papers

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  1. Truncated automatic sparse differentiation for machine learning interatomic potentials

    Sep 17, 2026Marcel F. Langer, Adrian Hill, Michele CeriottiInteratomic PotentialsMolecular Dynamics

  2. Correlation-Free Transition Path Sampling through Shooting Point Generation Guided by Committor Learning

    Sep 17, 2026Maximilian Negedly, Sebastian Falkner, Alessandro Coretti +1Markovian SamplingBoltzmann Distributions

  3. METALICA: METAdynamics and repLICA exchange for enhanced diffusion sampling

    Sep 15, 2026Alireza Omidi, Jiajun He, Jörg Gsponer +1Markov Chain Monte CarloDiffusion Sampling

  4. Machine learning kinetics from molecular dynamics data

    Sep 15, 2026Jonathan Weare, Aaron R. DinnerMolecular DynamicsReaction

  5. Neural-Network Solutions to Real-Space Charge Density and Generalization

    Sep 14, 2026Yuxuan Zeng, Taoyuze Lv, Zhicheng ZhongDensity Functional TheoryLarge-Scale Electronic Structure Calculations

  6. Prescreening Point Defects in Semiconductors With Machine Learning

    Sep 13, 2026Paul Karlsson, Joel Davidsson, Rickard ArmientoDensity Functional TheorySemiconductor Manufacturing

  7. El Agente Potente: High-Throughput Agentic Atomistic Simulations

    Sep 13, 2026Tsz Wai Ko, Jiaru Bai, Thomas Swanick +6Interatomic PotentialsMolecular Dynamics

  8. Autonomous Chemical Mechanistic Discovery through Agentic Reasoning and Validation

    Sep 12, 2026Dong Li, Sixuan Mi, Zihao Ye +10ReactionComputational Chemistry

  9. MLIP Detective: Active Failure Mode Discovery Beyond Benchmark Scores for Machine-Learning Interatomic Potentials

    Sep 8, 2026Ryuhei Okuno, Nontawat Charoenphakdee, Kaoru Hisama +1Interatomic PotentialsFailure Mechanism

  10. Equivariance Breaks the Learning Rate

    Sep 8, 2026Andrei Manolache, Mathias NiepertAdamEquivariant Neural Networks

  11. Hessian-based molecular conformation augmentation for a scalable and efficient strategy of machine learning interatomic potentials

    Sep 4, 2026Bumju Kwak, Jeonghee JoInteratomic PotentialsConformational Ensembles

  12. Generative Nested Sampling of Atomistic Thermodynamic Landscapes

    Sep 2, 2026Alessandro Coretti, Nico Unglert, Sebastian Falkner +2Molecular DynamicsBinary Black Hole Mergers

  13. TRACE: Spatiotemporal Contact Memory Graph Network Simulator for Granular Dynamics

    Sep 2, 2026Changjian Zhou, Negin Yousefpour, Jie Qi +3Contact ForcesFinite Element Method

  14. Mesh-Native Physics-Informed Graph Surrogates for TCAD-in-the-Loop Design Space Exploration

    Sep 2, 2026Leonid Popryho, Ayoub Sadeghi, Inna Partin-VaisbandFirst-Principles Calculation

  15. Physics-Informed Neural Network Surrogate for Oxygen Vacancy Dynamics in epitaxial SrTiO3\mathrm{SrTiO_3} on Si memristors via Dynamic Spectral Optimization

    Sep 2, 2026Rodion Podorozhny, Nikoleta Theodoropoulou, Jelena TešićResistive Random Access MemoryConventional Physics-Informed Neural Networks

  16. FrOGS: Discrete Neural Sampler for Independent Alloy Configurations Across Chemical Conditions

    Sep 1, 2026Kyucheol Min, Elyssa Hofgard, Tess SmidtMolecular Dynamics

  17. Latent unified smooth Hamiltonians for excited state chemistry

    Sep 1, 2026David Juergens, Martin Stöhr, Andreas E. Hillers-Bendtsen +2Computational ChemistryMolecular Dynamics

  18. Agentic programs: an emerging form of scientific software in computational materials science

    Sep 1, 2026Yunsung Lim, Haekwan Jeon, Jaesun Kim +2Molecular DynamicsScientific Discovery

  19. Why Multi-Layer Message Passing Works: Completeness Theory for Graph Neural Network Interatomic Potentials

    Sep 1, 2026Pingbing Ming, Han WangInteratomic PotentialsMessage Passing Neural Networks

  20. AdaptNTK: Adaptive Uncertainty Quantification and Active Learning for Neural Network Potentials

    Aug 31, 2026Prajwal Ananth, Shuwen YueInteratomic PotentialsActive Learning

  21. Toward a First-Principles Update Geometry for the Language-Model Head

    Aug 23, 2026Aditya Somasundaram, Charles Guille-Escuret, Alexander Moreno +2Spectral NormMulti-Head Self-Attention

  22. Equivariant learning of a transferable three-dimensional classical density functional

    Aug 13, 2026Bingqing ChengDensity Functional TheoryStatistical Mechanics

  23. An Agentic Workflow for Legacy HPC Modernization: Converting the Two-Electron-Integral Core of GAMESS

    Aug 12, 2026Yuzhong Shen, Masha Sosonkina, Peng Xu +1Agentic WorkflowsLarge-Scale Electronic Structure Calculations

  24. DynaPPI: A Large-scale Dynamic Protein Dataset for AI-driven Advances in Protein Interactomics

    Aug 11, 2026Jiabao Wei, Zilong Geng, Yuze Wang +5ProteinMolecular Dynamics

  25. Agent-MD: Selective LLM Intervention with Event-Driven Escalation for Stateful GCMC--MD Campaigns

    Aug 7, 2026Yijie Wang, Zhen-Yu Yin, Zhenheng Tang +1Molecular DynamicsAgent Framework

  26. A Multi-Agent Framework for Automated Coarse-Grained Molecular Dynamics of Polymers

    Aug 7, 2026Joohee Choi, Junhyeong Lee, Seunghwa RyuPolymerMolecular Dynamics

  27. Density-Functional Excited-State Gradients and Nonadiabatic Couplings on a Consumer GPU from a Contraction-DAG

    Aug 6, 2026Rubén Darío GuerreroDensity Functional TheoryContraction

  28. When May a Model Replace the Experiment? Audits, Licenses, and the Price of Trust in Surrogate-Driven Design

    Aug 2, 2026Shuangxiu, Ma, Wenhe +1Accurate Surrogate ModelsAlgorithm Auditing

  29. A Physics-Chemistry-Informed Neural Network (PCINN) for Real-Time Spatial-ALD Coverage Prediction and Reliable Kinetics Inversion

    Jul 31, 2026Ning Hu, Chang Liu, Yunlei Jiang +1Conventional Physics-Informed Neural NetworksAdvection-Reaction-Diffusion

  30. Ordered-to-disordered transfer learning with graph neural networks for formation-energy and HOMO-LUMO gap prediction in high-entropy perovskite oxides

    Jul 31, 2026Panupol Untarabut, Narjes Jomaa, Sylvian Cadars +4Graph Neural NetworksComputational Chemistry

  31. DreamQAS: Learning a Decision-Useful World Model for VQE-Efficient Quantum Architecture Search

    Jul 31, 2026Jiayang Niu, Yan Wang, Jie Li +4Variational Quantum CircuitsComputational Chemistry

  32. MDArena: Evaluating Coding Agents on Realistic Molecular Dynamics Workflows

    Jul 31, 2026Nithishwer Mouroug Anand, Wei-Tse Hsu, Kyle Vaccaro +6Coding AgentsMolecular Dynamics

  33. Implicit Machine Learning Force Fields Accelerate Molecular Dynamics Simulations

    Jul 31, 2026Johannes Maeß, Leon Werner, J. Thorben Frank +5Molecular DynamicsMachine Learning

  34. Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation

    Jul 30, 2026Paul Hagemann, Katharina Ueltzen, Simon Müller +2Crystal StructureInteratomic Potentials

  35. Chem World: A Large-Scale Benchmark and Physics-Informed Framework for Trustworthy Chemical Property Prediction

    Jul 30, 2026Tianyou Bai, Huan Wang, Mingchen Gao +4Molecular Property PredictionComputational Chemistry

  36. Using large language models to probe the limits of atom-centered structural descriptors

    Jul 29, 2026Michelangelo Domina, Michele CeriottiAtomsMolecular Property Prediction

  37. Recursive transformers for semiconductor thermo-mechanical reliability

    Jul 28, 2026Kart-leong LimUnified TransformerSurrogate Models

  38. Accurate structural modeling of chemically diverse molecular interfaces with Vilya-2

    Jul 28, 2026Vilya Research, :, Pascal Sturmfels +10Cyclic PeptidesStructure-Based Drug Design

  39. An Ontology for Machine Learning Interatomic Potentials

    Jul 25, 2026Daniel Hernández, Jong Hyun Jung, Yuji Ikeda +11Interatomic PotentialsDensity Functional Theory

  40. Learning to Prepare Molecular Ground States with Transformer Models

    Jul 24, 2026Alex Koziell-Pipe, Jasmine Brewer, Jem Guhit +14Quantum Circuit SimulationN$-Qubit Stabilizer States

  41. Graph-Theoretic Neural Network Fragmentation with Covariant Direct Molecular Force Learning: Enabling Coupled-Cluster Accuracy AIMD for Fluxional Systems

    Jul 23, 2026Xiao Zhu, Srinivasan S. IyengarMolecular DynamicsComputational Chemistry

  42. Machine-Learned Compact Subspace Generation for Quantum Selected Configuration Interaction within Density Matrix Embedding Framework

    Jul 22, 2026Ashish Kumar Patra, Anurag K. S. V., Ruchika Bhat +3Computational ChemistryStructure-Based Drug Design

  43. ATLAS: A Foundation Neural Sampler for Amorphous Materials

    Jul 21, 2026Mouyang Cheng, Denis Blessing, Botao Yu +4Molecular DynamicsMaterials Science

  44. Mapping Order in Semicrystalline Polymers using Machine Learning of Nanobeam Electron Diffraction

    Jul 18, 2026Nicholas Marchese, Arthur R. C. McCray, Yael Tsarfati +4Cryo-Electron MicroscopyTransmission Electron Microscopy

  45. Implementations of Quantum and Classical Topology-Aligned Architectures for Molecular Property Prediction

    Jul 15, 2026James T. Pegg, Hubert Okadome Valencia, Ronin WuQuantum Machine LearningComputational Chemistry

  46. DeepCormack: Fermi surface tomography using model-based data-driven algorithms

    Jul 14, 2026Georg F. B. Lovric, Bryn Drury, Carola-Bibiane Schönlieb +2TomographyHigh-Fidelity Surface Reconstruction

  47. Transferable Implicit Solvent Machine Learning Potential for Drugs and Proteins Approaching Ab Initio Accuracy

    Jul 12, 2026Jan Eckwert, Julija ZavadlavPrevious Machine-Learning-Based Implicit SolventInteratomic Potentials

  48. Edge Cluster Expansion with Radial Rotary Attention for Interatomic Potentials

    Jul 12, 2026Zemin Xu, Wenbo Xie, P. HuInteratomic PotentialsLie Group

  49. Active rejection enables reliable generalization of universal machine-learning interatomic potentials

    Jul 10, 2026Mingxiang Luo, Xinnan Mao, Lu Wang +3Interatomic PotentialsMolecular Dynamics

  50. A First-Principles Theory of Slow Thinking and Active Perception

    Jul 9, 2026Hongkang Yang, Zhi-Qin John Xu, Feiyu Xiong +1Cognitive ScienceThinking

  51. FirstResearch: Auditable Question Formation for LLM Scientific Discovery Agents

    Jul 6, 2026Yufeng WangAutoresearchPersonalized Large Language Model Agents

  52. EquiFiLM: Charge-Conditioned Equivariant Force Fields via Feature-wise Linear Modulation

    Jul 6, 2026Samuel Sahel-Schackis, Ken-ichi Nomura, Aiichiro Nakano +2Large-Scale Electronic Structure CalculationsWireless Foundation Models

  53. Physically-Relevant Information Learning in High-Dimensional Time-Derivatives Spaces

    Jul 6, 2026Domiziano Doria, Matteo Becchi, Giovanni M. PavanHigh-Dimensional DataAutomatic Differentiation

  54. AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms

    Jul 3, 2026Emmanuel Bengio, Sanjeev Raja, Yui Tik Pang +5Molecular DynamicsPrevious Machine-Learning-Based Implicit Solvent

  55. Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials

    Jul 2, 2026Gil Harari, Yoel Zimmermann, Ola Tangen Kulseng +4Interatomic PotentialsAdam

  56. Q-Score: A Quantum-Native Scoring Function for Molecular Docking

    Jul 2, 2026Kangyu Zheng, Yidong Zhou, Ruihao Li +3Structure-Based Drug DesignQuantum Approximate Optimization Algorithm

  57. Spin-Weighted Spherical Harmonics Enable Complete and Scalable E(3)\mathrm{E}(3)-Equivariant Networks

    Jul 1, 2026Chenxing Liang, Yuchao Lin, Andrii Kryvenko +5Equivariant Neural NetworksMolecular Dynamics

  58. Revisiting the Volume Hypothesis

    Jun 30, 2026Ari Pakman, Lior Kreimer, Yakir BerchenkoStochastic Gradient DescentGeneralisation

  59. Diffusion-warm sampling of the XY model enables fast thermalization at scale

    Jun 29, 2026Sehmimul Hoque, Roger Melko, Pooya RonaghTwo-Dimensional Ising ModelMarkov Chain Monte Carlo

  60. Bridging the NISQ and Fault-Tolerant Regimes: Generative-ML-Assisted Quantum Selected CI for Molecular Simulations

    Jun 29, 2026Anurag K. S. V., Ashish Kumar Patra, Manas Mukherjee +4Computational ChemistryStructure-Based Drug Design